| Human Factors | Other Factors |
|---|---|
| Participant behavior | Equipment failures |
| Evaluator errors | Records/Databases |
| Partner behavior | Unusual Events |
Presentation to MSU Department of Psychology, Program Evaluation Occasional Speaker Series, East Lansing, MI
2024-12-05
Missing data (MD) are measurements you intended to collect but did not get.
Data collection doesn’t always go according to plan…
| Human Factors | Other Factors |
|---|---|
| Participant behavior | Equipment failures |
| Evaluator errors | Records/Databases |
| Partner behavior | Unusual Events |
Handling missing data well enacts our guiding principles[1]:
In appropriate handling of missing data can cause analyses to yield biased results.
Misalignment of analyzed sample and intended population
Most statistical software defaults to listwise deletion of cases that have any missing values on the variables involved in an analysis. That reduces statistical
MCAR is when neither observed nor unobserved variables predict which data is missing
[3]
An ounce of prevention is better than a pound of cure